Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Certo v1 (AltSlate Labs) is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Certo v1 (AltSlate Labs) vs Kimi K3
Updated September 30, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 0
- Certo v1 (AltSlate Labs) only
- 2
- Kimi K3 only
- 48
- Like-for-like categories
- 0 / 8
Supported: Kimi K3How the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Certo v1 (AltSlate Labs) is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
Not enough matched evidence
A complete context comparison is not sourced.
Confidence: limitedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
—Certo v1 (AltSlate Labs)61.4Kimi K3
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 Certo v1 (AltSlate Labs) only
48 Kimi K3 only
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Agentic
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- 67.8
- Supported · #10/119
- Basis
- BenchAlign v5.8 lane · 0 vs 12 public rows
- Reading
- Not comparable
Coding
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- 61.4
- Supported · #18/144
- Basis
- BenchAlign v5.8 lane · 0 vs 14 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- 65.8
- #18/27
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- 89.4
- #1/49
- Basis
- Provisional lane · 0 vs 3 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- 67.8
- Supported · #18/170
- Basis
- BenchAlign v5.8 lane · 0 vs 6 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Certo v1 (AltSlate Labs)
- Not ranked
- Kimi K3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Certo v1 (AltSlate Labs) | Kimi K3 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 67.8Supported · #10/119 | Not comparableBenchAlign v5.8 lane · 0 vs 12 public rows | Not comparable |
| Coding | Not ranked | 61.4Supported · #18/144 | Not comparableBenchAlign v5.8 lane · 0 vs 14 public rows | Not comparable |
| Reasoning | Not ranked | 65.8#18/27 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | 89.4#1/49 | Not comparableProvisional lane · 0 vs 3 weighted rows | Not comparable |
| Knowledge | Not ranked | 67.8Supported · #18/170 | Not comparableBenchAlign v5.8 lane · 0 vs 6 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Certo v1 (AltSlate Labs)
- API rate not published
- Fit state unavailable
- Kimi K3
- $0.0105
- Fits in one request
Certo v1 (AltSlate Labs) has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Certo v1 (AltSlate Labs)
- API rate not published
- Fit state unavailable
- Kimi K3
- $0.195
- Fits in one request
Certo v1 (AltSlate Labs) has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Certo v1 (AltSlate Labs)
- API rate not published
- Fit state unavailable
- Cached-input rate unavailable
- Kimi K3
- $0.27
- Fits in one request
Certo v1 (AltSlate Labs) has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationCerto v1 (AltSlate Labs)Kimi K3
Context window
Maximum documented context; output-token limits may be lower.
Certo v1 (AltSlate Labs)
Not sourced
Kimi K3
1.05M
API model ID
Certo v1 (AltSlate Labs)
Not sourced
Kimi K3
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Certo v1 (AltSlate Labs)
No comparable hosted API rate
Provider pricingKimi K3
$0.3 per 1M cached input tokens
Documented inputs
Certo v1 (AltSlate Labs)
Not sourced
Kimi K3
Not sourced
Documented outputs
Certo v1 (AltSlate Labs)
Not sourced
Kimi K3
Not sourced
Provider availability
Certo v1 (AltSlate Labs)
Not sourced
Kimi K3
Not sourced
Reasoning profile
Certo v1 (AltSlate Labs)
Non-Reasoning
Kimi K3
Reasoning
Weight access
Certo v1 (AltSlate Labs)
Open Weight
Kimi K3
Pending
License
Certo v1 (AltSlate Labs)
Open Weight
Kimi K3
Pending
Release date
Certo v1 (AltSlate Labs)
Not sourced
Kimi K3
2026-07-16
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- A complete documented context comparison is not available.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Certo v1 (AltSlate Labs) or Kimi K3?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Certo v1 (AltSlate Labs) or Kimi K3?
Certo v1 (AltSlate Labs) is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Certo v1 (AltSlate Labs) or Kimi K3?
Certo v1 (AltSlate Labs) is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Certo v1 (AltSlate Labs) or Kimi K3?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Certo v1 (AltSlate Labs) or Kimi K3?
A complete documented context-window comparison is not available.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence50 rows
Agentic
Terminal-Bench 2.1
Certo v1 (AltSlate Labs)—Kimi K388.3%SourceNot directly comparable
BrowseComp
Certo v1 (AltSlate Labs)—Kimi K391.2%SourceNot directly comparable
DeepSearchQA
Certo v1 (AltSlate Labs)—Kimi K395.0%SourceNot directly comparable
Toolathlon-Verified
Certo v1 (AltSlate Labs)—Kimi K373.2%SourceNot directly comparable
MCP Atlas
Certo v1 (AltSlate Labs)—Kimi K384.2%SourceNot directly comparable
AutomationBench
Certo v1 (AltSlate Labs)—Kimi K330.8%SourceNot directly comparable
JobBench
Certo v1 (AltSlate Labs)—Kimi K352.9%SourceNot directly comparable
APEX-Agents
Certo v1 (AltSlate Labs)—Kimi K337.6%SourceNot directly comparable
SpreadsheetBench 2
Certo v1 (AltSlate Labs)—Kimi K334.8%SourceNot directly comparable
DECK-Bench
Certo v1 (AltSlate Labs)—Kimi K373.5%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Certo v1 (AltSlate Labs)—Kimi K380.9%SourceNot directly comparable
ApprenticeBench
Certo v1 (AltSlate Labs)—Kimi K318%SourceNot directly comparable
Coding
DeepSWE
Certo v1 (AltSlate Labs)—Kimi K367.5%SourceNot directly comparable
cursorBench32
Certo v1 (AltSlate Labs)—Kimi K360.8%SourceNot directly comparable
FrontierSWE
Certo v1 (AltSlate Labs)—Kimi K381.2%SourceNot directly comparable
ProgramBench
Certo v1 (AltSlate Labs)—Kimi K377.8%SourceNot directly comparable
Kimi Code Bench v2
Certo v1 (AltSlate Labs)—Kimi K372.9%SourceNot directly comparable
sweMarathon
Certo v1 (AltSlate Labs)—Kimi K342%SourceNot directly comparable
PostTrain Bench
Certo v1 (AltSlate Labs)—Kimi K336.6%SourceNot directly comparable
MLS-Bench Lite
Certo v1 (AltSlate Labs)—Kimi K348.3%SourceNot directly comparable
VulcanBench v3
Certo v1 (AltSlate Labs)—Kimi K373.7%SourceNot directly comparable
OpenHarmony Bench
Certo v1 (AltSlate Labs)—Kimi K357.3%SourceNot directly comparable
FrontierSWE v2
Certo v1 (AltSlate Labs)—Kimi K325.9%SourceNot directly comparable
LiveCodeBench (Vals)
Certo v1 (AltSlate Labs)—Kimi K387.2%SourceNot directly comparable
SWE-bench (Vals)
Certo v1 (AltSlate Labs)—Kimi K393.4%SourceNot directly comparable
PostTrainBench v1.1
Certo v1 (AltSlate Labs)—Kimi K332.0%SourceNot directly comparable
Reasoning
JevBench 1.4
Certo v1 (AltSlate Labs)0.00SourceKimi K3—Not directly comparable
JevBench 1.5
Certo v1 (AltSlate Labs)0.00SourceKimi K3—Not directly comparable
ARC-AGI-1
Certo v1 (AltSlate Labs)—Kimi K394.50%SourceNot directly comparable
ARC-AGI-2
Certo v1 (AltSlate Labs)—Kimi K360.4%SourceNot directly comparable
Multimodal
OfficeQA Pro
Certo v1 (AltSlate Labs)—Kimi K363.3%SourceNot directly comparable
MMMU-Pro
Certo v1 (AltSlate Labs)—Kimi K381.6%SourceNot directly comparable
MMMU-Pro w/ Python
Certo v1 (AltSlate Labs)—Kimi K383.4%SourceNot directly comparable
CharXiv w/o tools
Certo v1 (AltSlate Labs)—Kimi K384.8%SourceNot directly comparable
CharXiv
Certo v1 (AltSlate Labs)—Kimi K391.3%SourceNot directly comparable
MathVision
Certo v1 (AltSlate Labs)—Kimi K394.3%SourceNot directly comparable
MathVision w/ Python
Certo v1 (AltSlate Labs)—Kimi K397.8%SourceNot directly comparable
BabyVision w/ Python
Certo v1 (AltSlate Labs)—Kimi K385.7%SourceNot directly comparable
ZeroBench
Certo v1 (AltSlate Labs)—Kimi K323.0%SourceNot directly comparable
ZeroBench w/ Python
Certo v1 (AltSlate Labs)—Kimi K341.0%SourceNot directly comparable
WorldVQA ForceAnswer
Certo v1 (AltSlate Labs)—Kimi K351.0%SourceNot directly comparable
OmniDocBench
Certo v1 (AltSlate Labs)—Kimi K391.1%SourceNot directly comparable
PerceptionBench
Certo v1 (AltSlate Labs)—Kimi K358.5%SourceNot directly comparable
Knowledge
GPQA
Certo v1 (AltSlate Labs)—Kimi K393.5%SourceNot directly comparable
GPQA-D
Certo v1 (AltSlate Labs)—Kimi K393.5%SourceNot directly comparable
HLE
Certo v1 (AltSlate Labs)—Kimi K356%SourceNot directly comparable
HLE w/o tools
Certo v1 (AltSlate Labs)—Kimi K343.5%SourceNot directly comparable
GPQA Diamond (Vals)
Certo v1 (AltSlate Labs)—Kimi K392.9%SourceNot directly comparable
MMLU-Pro (Vals)
Certo v1 (AltSlate Labs)—Kimi K388.0%SourceNot directly comparable
Instruction following
Gray Swan IPI (15 attempts)
Certo v1 (AltSlate Labs)—Kimi K352.7%SourceNot directly comparable
50 public results · 0 shared
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Last updated September 30, 2026